What if you could build your own AI-powered customer support platform? Something that feels like intercom but runs on your stack with voice agents, AI, and multi-tenant B2B baked in. This is Echo, and in this full course, you'll build it from scratch. The AI handles support on its own and knows when to escalate. If a customer gets frustrated, Echo flags the chat for a human.
And if the issue resolves itself, Echo closes it. All of this is powered by convex agents, retrieval-augmented generation, and any AI model of your choice, including OpenAI, Gemini, Anthropic, or Grok. Inside the dashboard, support teams see everything in real-time. They can take over conversations, respond directly, or resolve manually. You'll also get full context, like user info, device, and session history.
Echo can learn your product by reading your documentation. No model tuning needed. The AI generates embeddings and uses retrieval-augmented generation to ground its responses. Echo supports voice agents, phone numbers, as well as inbound and outbound phone calls, all powered by WAPI. And you'll learn how to white-label a single-tenant voice API into a B2B SaaS using Bring Your Own Keys method, along with AWS Secrets Manager to store API credentials securely per tenant.
Let's hear the voice agent in action. Hello, you've reached FapiBank customer support. My name is Tom. How may I assist you today? Hey, yeah, I want to check my account balance.
Could you provide the last four digits of your phone number so I can verify your account? Sure. 1, 2, 3, 4. Thank you, John Doe. Your current account balance is $2, 534.67.
Is there anything else I can assist you with today? That's it. Thank you. Echo comes with built-in billing, powered by Clerk. You can start for free with one teammate and human-only chat.
And you can upgrade to unlock AI features, voice agents, knowledge base, and full customization as well as multiple team members, making this app fully self-sustainable. Every Echo account is scoped to an organization. You can invite team members, assign roles, and manage workspaces. All isolated, secure, and powered by Clerc. Thanks to Sentry, our app can track errors with full stack visibility.
We can get real-time alerts, replay sessions, and trace logs across frontend and backend, as well as a seamless integration with Convex. This brings our app one step closer to a production-grade application. Echo runs in a TurboRepo Monorepository, with separate apps and shared packages. We are going to develop not one, not two, but three different apps. The dashboard for our operator dashboard, the widget for our chatbox, and an embed application, which will be our dedicated developer toolkit to preview our widget script.
Along those three apps, we're going to share our convex package and our Shatzian UI components, making this a true monorepo architecture. Each chapter in this tutorial wraps up with a real pull request, reviewed by CodeRabbit, ensuring that our code has no bugs or serious security issues, allowing us to ship production-grade code. This isn't just a tutorial. It's a blueprint for a real SaaS business, with AI, voice agents, billing, and auth, ready to serve real customers. This is how you build a modern SaaS product in 2025.
And now, without further ado, let's build Echo.